Abstract—In this paper we discuss the stroke rehabilitation by robotic device and a novel exoskeleton, which is based on the patient's self-guided control will be presented. It is realized by moving the patient’s own healthy arm in order to provide the movement trajectories for the exoskeleton. The main advantage of the exoskeleton is its flexibility and adaptivity for individual patient’s rehabilitation training. A new model predictive control (MPC) algorithm for handling coupling and nonlinearity is also proposed and a microprocessor-based drive system for the exoskeleton will be adopted. In addition, to measure the angular positions corresponding to the joint angles of arm high resolution potentiometers are used.

Index Terms—Stroke rehabilitation, exoskeleton, model predictive control, motor control.

Jiajia Hu and Xinmin Xu are with Department of Information Science and Electronic Engineering, Zhejiang University, 310027, China (e-mail: hujiajia131@gmail.com, xuxm@zju.edu.cn).
Weidong Liu is with Department of Electronic and Computer Engineering, Ngee Ann Polytechnic, 599489, Singapore (e-mail: lwe6@np.edu.sg).

 

Cite:Jiajia Hu, Xinmin Xu, and Weidong Liu, "Exoskeleton to Rehabilitate Paralyzed Arm Based on Patient Healthy Arm Guidance," International Journal of Bioscience, Biochemistry and Bioinformatics vol. 3, no. 3, pp. 161-166, 2013.